Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
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Article Experimental Investigation of Refractive Index Measurement of Common Solvents and Aqueous Solutions in the Infrared Wavelengths(2018) Yüksel, K.; İde, CWe proposed and experimentally demonstrated a fast and simple technique to measure refractive index of liquids. A commercial Optical Time-Domain Reflectometer (OTDR) was implemented for interrogating sensor tips from a remote location. The system uses Fresnel reflected light from standard single mode fiber tips as sensing points without requiring any chemical coating, delicate fiber components, and/or sophisticated architecture at the sensor head. We reported new measurements of refractive indices of common solvents and solutions at both 1550 nm and 1625 nm. The precision of the proposed measurement system was found to be in the order of 10-4. The experimental results have been validated by the way of theoretical calculations.Article Citation - WoS: 2Citation - Scopus: 2Subwavelength Thickness Characterization of Curved Dielectric Films Exploiting Spatially Structured Entangled Photons(Optica Publishing Group, 2023) Ataç, Enes; Dinleyici, Mehmet SalihPrecise determination of thin dielectric film optical properties is a critical issue for fiber optic sensor technologies. However, conventional methods for the optical characterization of these films not only are generally complex and tedious processes on curved surfaces but also require well-calibrated and overly sophisticated devices. We, on the other hand, propose a novel and practical quantum-based phase diffraction scheme to characterize the thickness of ultra-thin transparent dielectric films coated on an optical fiber beyond the classical diffraction limits in this paper. The approach is implemented by evaluating the effect of thickness variations on the highly visible two-photon diffraction pattern's zero crossings and amplitudes. The mathematical model and numerical simulations con-tribute to a better understanding of how the spatially structured entangled photons improve thickness precision with the help of intensity correlations and a confocal aperture. To prove the impact of the proposed system, it is compared with the classical phase diffraction method in the literature via simulations. According to the results, the thickness of the transparent dielectric films can be accurately estimated below one-twentieth of the wavelength of interest. & COPY; 2023 Optica Publishing GroupArticle Citation - WoS: 3Citation - Scopus: 4Cost-Effective Experiments With Additively Manufactured Waveguide and Cavities in the S-Band(Iop Publishing Ltd, 2023) Karatay, Anıl; Yilmaz, Hasan Önder; Özkal, Ceren; Yaman, FatihThis study demonstrates the applicability of additively manufactured components that are metalized with conductive tape for two different microwave experiments. We focus on dielectric measurements and prototyping elliptical accelerator cavities at a low power regime for 2.45 GHz. To illustrate the accuracy of our results for the commonly used solid/liquid materials in engineering and to compare the fundamental accelerator cavity parameters with previous research rectangular and elliptic 3D-printed cavities coated with aluminum-type tape were employed in the experiments. Results reported for the complex-valued permittivities and specific design parameters for the cavity prototype are consistent with the literature. Various approaches to obtain the conductivity value of the tape and the effect of the roughness/thickness of the coating on the reflection parameter are discussed in detail. We confirm the effectiveness of the proposed approach, which reduces costs and provides a high degree of accuracy for investigated applications.Article Citation - WoS: 9Citation - Scopus: 12Intensity and Phase Stacked Analysis of a 40-Otdr System Using Deep Transfer Learning and Recurrent Neural Networks(Optica Publishing Group, 2023) Kayan, Ceyhun Efe; Yüksel Aldoğan, Kıvılcım; Gümüş, AbdurrahmanDistributed acoustic sensors (DAS) are effective apparatuses that are widely used in many application areas for recording signals of various events with very high spatial resolution along optical fibers. To properly detect and recognize the recorded events, advanced signal processing algorithms with high computational demands are crucial. Convolutional neural networks (CNNs) are highly capable tools to extract spatial information and are suitable for event recognition applications in DAS. Long short-term memory (LSTM) is an effective instrument to process sequential data. In this study, a two-stage feature extraction methodology that combines the capabilities of these neural network architectures with transfer learning is proposed to classify vibrations applied to an optical fiber by a piezoelectric transducer. First, the differential amplitude and phase information is extracted from the phasesensitive optical time domain reflectometer (40-OTDR) recordings and stored in a spatiotemporal data matrix. Then, a state-of-the-art pre-trained CNN without dense layers is used as a feature extractor in the first stage. In the second stage, LSTMs are used to further analyze the features extracted by the CNN. Finally, a dense layer is used to classify the extracted features. To observe the effect of different CNN architectures, the proposed model is tested with five state-of-the-art pre-trained models (VGG-16, ResNet-50, DenseNet-121, MobileNet, and Inception-v3). The results show that using the VGG-16 architecture in the proposed framework manages to obtain a 100% classification accuracy in 50 trainings and got the best results on the 40-OTDR dataset. The results of this study indicate that pre-trained CNNs combined with LSTM are very suitable to analyze differential amplitude and phase information represented in a spatiotemporal data matrix, which is promising for event recognition operations in DAS applications. (c) 2023 Optica Publishing GroupArticle Citation - WoS: 4Citation - Scopus: 5Toward Safe and High-Performance Human-Robot Collaboration Via Implementation of Redundancy and Understanding the Effects of Admittance Term Parameters(Cambridge University Press, 2022) Kanık, Mert; Ayit, Orhan; Dede, Mehmet İsmet Can; Tatlıcıoğlu, EnverSummary Today, demandsin industrial manufacturing mandate humans to work with large-scale industrial robots, and this collaboration may result in dangerous conditions for humans. To deal with this situation, this work proposes a novel approach for redundant large-scale industrial robots. In the proposed approach, an admittance controller is designed to regulate the interaction between the end effector of the robot and the human. Additionally, an obstacle avoidance algorithm is implemented in the null space of the robot to prevent any possible unexpected collision between the human and the links of the robot. After safety performance of this approach is verified via simulations and experimental studies, the effect of the parameters of the admittance controller on the performance of collaboration in terms of both accuracy and total human effort is investigated. This investigation is carried out via 8 experiments by the participation of 10 test subjects in which the effect of different admittance controller parameters such as mass and damper are compared. As a result of this investigation, tuning insights for such parameters are revealed.Article Citation - WoS: 3Citation - Scopus: 3Automated Labeling of Cancer Textures in Larynx Histopathology Slides Using Quasi-Supervised Learning(Science Printers and Publishers Inc., 2014) Önder, Devrim; Sarıoğlu, Sülen; Karaçalı, BilgeOBJECTIVE: To evaluate the performance of a quasisupervised statistical learning algorithm, operating on datasets having normal and neoplastic tissues, to identify larynx squamous cell carcinomas. Furthermore, cancer texture separability measures against normal tissues are to be developed and compared either for colorectal or larynx tissues. STUDY DESIGN: Light microscopic digital images from histopathological sections were obtained from laryngectomy materials including squamous cell carcinoma and nonneoplastic regions. The texture features were calculated by using co-occurrence matrices and local histograms. The texture features were input to the quasisupervised learning algorithm. RESULTS: Larynx regions containing squamous cell carcinomas were accurately identified, having false and true positive rates up to 21% and 87%, respectively. CONCLUSION: Larynx squamous cell carcinoma versus normal tissue texture separability measures were higher than colorectal adenocarcinoma versus normal textures for the colorectal database. Furthermore, the resultant labeling performances for all larynx datasets are higher than or equal to that of colorectal datasets. The results in larynx datasets, in comparison with the former colorectal study, suggested that quasi-supervised texture classification is to be a helpful method in histopathological image classification and analysis.Conference Object Citation - Scopus: 13-D Switching Fabric Node Design(ACTA Press, 2004) Dinleyici, Mehmet Salih; Akın, OsmanIn this work we investigate an all-optical switching node that can be controlled by means of a transient grating, which is formed by interference of two Gaussian beams. This design considers 3-D architecture of switching fabrics.. real profile of Gaussian beams and fast switching time requirements. Four Wave Mixing (FWM) technique is applied in the evanescent field region of waveguide, showing chi((3)) nonlinearity. The formed grating is analysed by standart methods to obtain reflection coefficient and then coupling coefficient for power exchange between waveguides.Conference Object Detection of Urban Change Using Remote Sensing and Gis: Izmir Case(Taylor and Francis Ltd., 2008) Tarhan, Çiğdem; Arkon, Cemal; Çelik, M.; Gümüştekin, Şevket; Tecim, V.This study is an example of how land use changes could be detected via high resolution remotely sensed data. In order to perform "change detection" IKONOS satellite images, belonging to 2001 and 2004, have been used. An automated Graphical User Interface (GUI) has been created for detection of environment. Different image enhancement techniques and a fuzzy inference system have been combined in the GUI. The detection results are classified according to some basic levels such as 20-50% and 70%. Additionally, four different change detection algorithms have been applied which are pixel-based, object based, feature based. These algorithms have been examined according to change detection levels with different image enhancement techniques. At the end of the study, the results have been compared.Conference Object Citation - WoS: 1Distance Measurement by Means of a Groove Guide Oscillator(Electromagnetics Academy, 2009) Bechteler, Thomas F.; Aydınlık Bechteler, Ayşe SevinçIn this work, a system for measuring the distance between two metallic plates is presented. A groove guide resonator operating in the X-band with an incorporated Gunn element serves as the distance sensor. According to the distance between the two metallic plates, the resonant frequencies of the groove guide oscillator change. In a first step, the fundamental resonant frequency of the groove guide oscillator at various distances is computed by means of the FDTD (Finite Difference Time Domain) method. In a second step, the resonant frequencies of the realized groove guide oscillator were measured. Although the signal's wavelength is about 30 mm, the resolution of the measurement is in the sub-millimeter level, i.e., about 25 mu m. Furthermore, in case of distance variations, even within a short time, the system is able to track distance variations nearly instantaneously. The resonant frequency information is processed using a heterodyne system.Conference Object Citation - Scopus: 8Localization of a Passive Molecular Transmitter With a Sensor Network(Springer, 2020) Güleç, Fatih; Atakan, BarışMacroscale molecular communication (MC), which has a potential for practical applications, is a promising area for communication engineering. In a practical scenario such as monitoring air pollutants released from an unknown source, it is essential to estimate the location of the molecular transmitter (TX). This paper presents a novel Sensor Network-based Localization Algorithm (SNCLA) for passive transmission by using a novel experimental platform which mainly comprises a clustered sensor network (SN) with 24 sensor nodes and evaporating ethanol molecules as the passive TX. With the usage of the SN concept, novel methods can be developed for the problems in macroscale MC by utilizing the wide literature of sensor networks. In SNCLA, Gaussian plume model is employed to derive the location estimator. The parameters such as transmitted mass, wind velocity, detection time and actual concentration are calculated or estimated from the measured signals via the SN to be employed as the input for the location estimator. The numerical results show that the performance of SNCLA is better for stronger winds in the medium. Our findings show that evaporated molecules do not propagate homogeneously through the SN due to the presence of the wind. In addition, the estimation error of SNCLA decreases for higher detection threshold values. © 2020, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.